1. Field of the Invention
The present invention relates to an electroencephalogram interface system for inferring an intent of a user by utilizing an electroencephalogram. More specifically, the present invention relates to an electroencephalogram interface system having a function of confirming whether an inferred intent of a user (a selected option) is correct or not.
2. Description of the Related Art
Devices having various functions for use in daily life have been proposed. By using such devices, users may obtain desired information or enjoy the services provided by the devices.
In recent years, due to an increase in the number of devices themselves and an increase in the information that cannot be obtained without using devices, there have been increasing needs for facilitating a user's manipulation of an interface for allowing the user to give instructions for device manipulations. In information devices (television sets, mobile phones, PDAs, etc.), for example, a user makes device manipulations as he or she selects an option which is a manipulable item (menu item) on of the information device, while looking at the screen. As method for making such manipulation inputs, methods such as pressing a button, moving a cursor and making a confirmation, or manipulating a mouse while watching a screen have been used. However, it may have been impossible to execute a manipulation when both hands are unavailable, due to tasks other than device manipulations, e.g., household chores, rearing of children, and driving an automobile.
In answer thereto, there are input methods utilizing biological signals from a user. Donchin et al., “The Mental Prosthesis: Assessing the Speed of a P300-Based Brain-Computer Interface”, IEEE TRANSACTIONS ON REHABILITATION ENGINEERING, Vol. 8, No. 2, June 2000 discloses a technique that utilizes an event-related potential of an electroencephalogram for distinguishing an option which a user wishes to select. Specifically, options are randomly highlighted, and the waveform of an event-related potential (often referred to as a P300 component) which appears about 300 milliseconds after a point in time that an option that the user wishes to select was highlighted is utilized to enable an inference of an option.
As used herein, an “event-related potential” refers to a transient potential fluctuation in the brain, which is a portion of the electroencephalogram and which occurs in temporal relationship with an external or internal event.
According to this technique, even in a situation where both hands are full, or even in a situation where the user is unable to move his or her limbs due to an illness or the like, the user can select an option which they wish to select, whereby an interface for device manipulations, etc., can be realized. Also in Japanese Laid-Open Patent Publication No. 2004-275619 (an example of P300-BCI), an example of an electroencephalogram interface which similarly utilizes an event-related potential is described.
However, an electroencephalogram signal is a weak signal that has fluctuations, and contains a lot of noise. It is difficult to completely prevent mixing of noise. Oftentimes, a desired event-related potential cannot be obtained from a single electroencephalogram measurement, and it is not always the case that a user's intent can be accurately determined.
Therefore, a method is known which acquires an event-related potential over plural times under the same condition, and takes an arithmetic mean thereof, thus obtaining only a desired electroencephalogram component by counteracting noise components which occur unconditionally. In physiopsychological experimentation and the like, it is supposed that an event-related potential must be obtained through a summation over several dozens of times. For example, Hiroshi NITTONO, “Event-Related Potential Guidebook For Psychology”, Kitaoji Shobo, 2005, p. 69 states that “supposedly, in the case of a large potential exceeding 10 μV, such as the P3 (P300) which is the target of this measurement, a summation over about 20 times is required to obtain a stable waveform”.
FIG. 16 shows a relationship between the number of summations and the distinction ratio for an event-related potential in an electroencephalogram interface. FIG. 16 is FIG. 3 taken from Donchin et al., supra, being modified so that the horizontal axis reads as the number of summations.
In FIG. 16, the horizontal axis represents the number of summations, and the vertical axis represents the distinction ratio, in the electroencephalogram interface of Donchin et al., supra. The two lines shown in FIG. 16 represent results of different analysis methods. FIG. 16 would indicate that the distinction ratio improves as the number of summations is increased, and that a 100% distinction rate is not attained unless the number of summations is adequate. For example, although a near 100% distinction ratio is obtained from a summation over 16 times and 32 times, only a 30 to 50% distinction ratio is obtained from a summation over 1 or 2 times. It is reported in many distinction techniques that an about 80% to 90% distinction rate is achieved by using an arithmetic mean waveform over plural times. This situation means that, when an electroencephalogram interface is used, it is not guaranteed that the device can make a correct determination with respect to every manipulation. It means that one or two unsuccessful instances will be included among about ten manipulations.
Japanese Laid-Open Patent Publication No. 2005-34620 (a second example of P300-BCI, including also displaying of the number of summations) also discloses results of studying the number of summations for an event-related potential. In paragraph 0050 of Japanese Laid-Open Patent Publication No. 2005-34620, the number of summations is experimentally varied from 8 times to 22 times for each of five words. The experimental results in this case are shown in Table 2 at paragraph 0058 of Japanese Laid-Open Patent Publication No. 2005-34620. In this laid-open patent publication, it is reported that the number of summations that provides the highest distinction ratio is 10 to 20 times.
Basically, as the number of summations increases, noise influences are reduced and thus the distinction accuracy is expected to improve. However, as the number of summations increases, the amount of time that the user needs to pay attention to the interface increases. In Japanese Laid-Open Patent Publication No. 2005-34620, the options need to flicker as often as 100 times. While the options flicker 100 times, the test subject needs to wait for the very option of selection to be lit, and actually think that he or she wants to select it when it is lit. Thus, the test subject needs to maintain a conscious state of attention for a long time. The time required to make a selection depends on the flickering period. In this laid-open patent publication, it is supposed that 100 times of presentation take about one minute (paragraph 0050 of Japanese Laid-Open Patent Publication No. 2005-34620).
To summarize all of the above, it can be said that there is a trade off relationship between improving the distinction accuracy by increasing the number of summations and reducing the amount of time that the user pays attention to the interface by decreasing the number of summations.